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Recursive Self Improvement - Is AI About to Start Improving AI?

RSI

What happens when AI starts building the next generation of AI?

We spend a lot of time talking about what AI can do for us.

But there is a much bigger question emerging: What happens when AI starts helping to improve the technology that creates AI?

That is the idea behind Recursive Self Improvement (RSI).

AI systems are already being used to write code, run experiments, analyse results and contribute to AI research. We are not yet at a point where AI is independently redesigning itself and creating increasingly capable successors without human involvement.

But the boundary is moving. And that raises some fascinating questions. Could AI eventually improve AI research faster than humans can?

What happens to human oversight when AI becomes an increasingly active participant in its own development? Could the same AI systems that accelerate capability also help improve AI safety and alignment?

And what could this mean for CIOs, CTOs and technology leaders trying to plan for a future where the underlying capabilities of AI could themselves be accelerating?

In this Inspiring Tech Leaders episode, I explore the rise of Recursive Self Improvement, how it relates to AGI, the potential economic impact, the challenges around safety and governance, and what it could mean when AI begins to play a bigger role in creating the AI that follows it.

Available on: Apple Podcasts | Spotify | YouTube | All major podcast platforms


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Why Hugging Face Could Be Nvidia’s Most Important Acquisition

Nvidia and Hugging Face

Nvidia’s reported $12.9 billion acquisition of Hugging Face is about much more than buying another AI company.

At the heart of the deal is a much bigger strategic question, which is who controls the ecosystem where AI developers discover models, access datasets, experiment with tools and build the next generation of AI applications and agents?

Hugging Face has become one of the most important platforms in the 
AI and open source ecosystem, connecting developers with thousands of AI models, datasets, libraries and development tools.

For Nvidia, acquiring Hugging Face could extend its influence far beyond GPUs and AI infrastructure.
It could give Nvidia a much stronger position across the entire AI technology stack, from the infrastructure powering AI workloads to the platforms where developers choose the models and tools they use to build applications.

That raises some fascinating questions for technology leaders.
Could Nvidia be building the most powerful AI ecosystem in the world? What would the acquisition mean for AI developers, enterprise AI, generative AI and AI agents? Could Nvidia influence which AI models become widely adopted? And perhaps most importantly, what happens to open source AI, competition and neutrality if one of the world's most important AI infrastructure companies owns a platform at the centre of the developer ecosystem?

In this episode of 
Inspiring Tech Leaders, I explore Nvidia’s Hugging Face acquisition, the strategic motivations behind the deal and what it could mean for the future of AI.

If you are a 
CIO, CTO, technology leader, AI developer or technology strategist, this is a deal worth understanding.

Is Nvidia simply strengthening its AI ecosystem, or is it positioning itself to influence the future direction of artificial intelligence?


Listen to the episode and let me know what you think.

Available on: Apple Podcasts | Spotify | YouTube | All major podcast platforms

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GPT-6 Astra - What Happens When AI Becomes a Digital Employee?

GPT6

GPT-6 Astra is here and AI may have just taken another major step towards becoming a digital employee.

In this episode of Inspiring Tech Leaders, I take a look at OpenAI’s new GPT-6 Astra and what makes it different from the AI models we’ve become used to.

This isn’t simply about better answers. Astra is designed to reason, research, write code, use computers, browse the web and carry out increasingly complex tasks with much greater autonomy. And there’s another side to the story. OpenAI says Astra has reached a new threshold in cybersecurity capability, with the ability to identify previously unknown vulnerabilities and develop exploits when given the right tools and access.

So what happens when AI moves from responding to instructions to actually performing work?

I explore what this could mean for the future of work, cybersecurity, AI agents and enterprise technology, as well as the challenges around governance, monitoring and keeping humans in control. I also look at the rather messy rollout of GPT-6 Astra and a fascinating real-world test of GPT-6 Pro for job searching.

What do you think? Are we entering the era of the AI employee, or are we still some way from truly autonomous AI?

Available on: Apple Podcasts | Spotify | YouTube | All major podcast platforms

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The New Rules of AI - What Tech Leaders Must Know

EU AI Law

The EU AI Act has entered a new and important phase.

In this episode of the Inspiring Tech Leaders podcast, I explore what the 2 August 2026 milestone means for organisations using, deploying and supplying AI.

The discussion covers:
💡 Why transparency is becoming a core AI responsibility
💡 When people must be told they are interacting with AI
💡 New expectations around deepfakes and synthetic media
💡 The importance of machine-readable labelling and digital provenance
💡 Why every organisation needs an AI inventory
💡 The difference between AI providers and deployers
💡 How AI procurement is becoming part of supply-chain governance
💡 The potential penalties for getting transparency obligations wrong
💡 Whether responsible AI can become a competitive advantage rather than simply a compliance burden

The central message is simple – AI Governance should not be about stopping innovation. It should be about enabling organisations to innovate safely, transparently and responsibly.

Available on: Apple Podcasts | Spotify | YouTube | All major podcast platforms

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